Here comes ChatGPT for automation engineers and programmable logic controller (PLC) code generation. Siemens and Microsoft continue their longstanding strategic relationship with a new product focused on artificial intelligence (AI), combining Siemen’s Teamcenter software for product lifecycle management (PLM) with Microsoft’s Teams platform and the language models in Azure OpenAI Service. Together, AI-powered software development on the production line will enhance factory automation and quality inspection.
OpenAI’s ChatGPT and other Azure AI services, with Siemens’ industrial automation engineering solutions, can accelerate the work done by software developers and automation engineers. Using natural language inputs to generate PLC code can reduce time and errors. The AI solution can also identify errors for maintenance teams and generate step-by-step solutions.
“The integration of AI into technology platforms will profoundly change how we work and how every business operates,” said Scott Guthrie, executive vice president of Cloud + AI at Microsoft. “With Siemens, we are bringing the power of AI to more industrial organizations, enabling them to simplify workflows, overcome silos and collaborate in more inclusive ways to accelerate customer-centric innovation.”
“Powerful, advanced artificial intelligence is emerging as one of the most important technologies for digital transformation,” said Cedrik Neike, member of the managing board of Siemens AG and CEO Digital Industries. “Siemens and Microsoft are coming together to deploy tools like ChatGPT so we can empower workers at enterprises of all sizes to collaborate and innovate in new ways.”
The AI solutions are also focused on breaking down communication siloes between design engineers, frontline workers and teams across the business. Service engineers and production operators can use mobile devices to document and report product design or quality concerns using natural speech, and Azure OpenAI Service can parse informal speech data, automatically create a summarized report and route it within Teamcenter to the appropriate team member. Through Microsoft Teams, push notifications simplify the workflow process for requested design changes and speed up innovation cycles.
Early defect detection is also critical for efficient production and also where AI can enhance computer vision to scale quality control, identify product variances and make real-time adjustments. Machine learning systems can analyze camera and video images to build, deploy, run and monitor AI vision models on the shop floor.
The Siemens/Microsoft collaboration and joint innovation began more than 35 years ago covering projects with thousands of customers. Other areas of collaboration include predictive maintenance and cloud services.
Together at Hannover Messe, the two companies will demonstrate how AI-powered software development can enhance automation, product development and visual quality inspection. A specific session will focus on Microsoft Azure Machine Learning and Siemens’ Industrial Edge capability, to understand how machine learning analyzes camera and video images to build AI vision models.
